Abstract
Property-based testing is the process of selecting test data from user-specified properties fro testing a program. Current automatic property-based testing techniques adopt direct generate-and-test approaches for this task, consisting in generating first test data and then checking whether a property is satisfied or not. are generated at random and rejected when they do not satisfy selected coverage criteria. In this paper, we propose a technique and tool called FocalTest, which adopt a test-and-generate approach through the usage of constraint reasoning. Our technique utilizes the property to prune the search space during the test data generation process. A particular difficulty is the generation of test data satisfying MC/DC on the precondition of a property, when it contains function calls with pattern matching and high-order functions. Our experimental results show that a non-naive implementation of constraint reasoning on these constructions outperform traditional generation techniques when used to find test data for testing properties.
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Carlier, M., Dubois, C., Gotlieb, A. (2013). FocalTest: A Constraint Programming Approach for Property-Based Testing. In: Cordeiro, J., Virvou, M., Shishkov, B. (eds) Software and Data Technologies. ICSOFT 2010. Communications in Computer and Information Science, vol 170. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29578-2_9
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DOI: https://doi.org/10.1007/978-3-642-29578-2_9
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